TY - JOUR
T1 - SNAP-II predicts severe intraventricular hemorrhage and chronic lung disease in the neonatal intensive care unit
AU - Chien, Li Yin
AU - Whyte, Robin
AU - Thiessen, Paul
AU - Walker, Robin
AU - Brabyn, David
AU - Lee, Shoo K.
N1 - Funding Information:
This study was supported by grants 40503 and 00152 from the Medical Research Council of Canada. Additional funding was provided by the B.C. Children’s Hospital Foundation; Calgary Regional Health Authority; Division of Neonatology, Children’s Hospital of Eastern Ontario; Child Health Program, Health Care of St. John’s; The Neonatology Program, Hospital for Sick Children; Lawson Research Institute; Midland Walwyn Capital; Division of Neonatology, McMaster Health Sciences Centre; Mount Sinai Hospital; North York General Hospital Foundation; Saint Joseph’s Health Centre; University of Western Ontario; Women’s College Hospital.
PY - 2002
Y1 - 2002
N2 - Objective: To determine whether the Score for Neonatal Acute Physiology, Version II (SNAP-II), improved prediction of severe (≥grade III) intraventricular hemorrhage (IVH) and chronic lung disease (CLD) when compared to models using gestational age (GA) and traditional risk factors (e.g., Apgar score, small-for-gestational-age, sex, outborn status). Study Design: We examined 4226 infants ≤32 weeks' GA admitted to 17 Canadian neonatal intensive care units between 1996 and 1997. We compared prediction models for severe IVH and CLD, with and without SNAP-II. Results: SNAP-II was a significant and independent predictor of severe IVH and CLD. Addition of SNAP-II to models using GA and traditional risk variables significantly (p<0.05) improved model prediction (AUC 0.8 for severe IVH; 0.83 for CLD). Models were well calibrated (p>0.05 for Hosmer-Lemeshow goodness of fit test). Conclusion: Addition of SNAP-II to models using GA and traditional risk factors significantly improves prediction of severe IVH and CLD.
AB - Objective: To determine whether the Score for Neonatal Acute Physiology, Version II (SNAP-II), improved prediction of severe (≥grade III) intraventricular hemorrhage (IVH) and chronic lung disease (CLD) when compared to models using gestational age (GA) and traditional risk factors (e.g., Apgar score, small-for-gestational-age, sex, outborn status). Study Design: We examined 4226 infants ≤32 weeks' GA admitted to 17 Canadian neonatal intensive care units between 1996 and 1997. We compared prediction models for severe IVH and CLD, with and without SNAP-II. Results: SNAP-II was a significant and independent predictor of severe IVH and CLD. Addition of SNAP-II to models using GA and traditional risk variables significantly (p<0.05) improved model prediction (AUC 0.8 for severe IVH; 0.83 for CLD). Models were well calibrated (p>0.05 for Hosmer-Lemeshow goodness of fit test). Conclusion: Addition of SNAP-II to models using GA and traditional risk factors significantly improves prediction of severe IVH and CLD.
UR - http://www.scopus.com/inward/record.url?scp=85047698381&partnerID=8YFLogxK
U2 - 10.1038/sj.jp.7210585
DO - 10.1038/sj.jp.7210585
M3 - Article
C2 - 11840239
AN - SCOPUS:85047698381
SN - 0743-8346
VL - 22
SP - 26
EP - 30
JO - Journal of Perinatology
JF - Journal of Perinatology
IS - 1
ER -